Building And Managing Training Datasets For Ml With Snorkel

Building and Managing Training Datasets for ML with Snorkel PDF
Author: Alex Ratner
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Building And Managing Training Datasets For Ml With Snorkel

by Alex Ratner, Building And Managing Training Datasets For Ml With Snorkel Books available in PDF, EPUB, Mobi Format. Download Building And Managing Training Datasets For Ml With Snorkel books, One of the key bottlenecks in building ML systems is creating and managing the massive training datasets that today's models learn from. Alex Ratner outlines work on Snorkel, an open source framework for building and managing training datasets, and details three key operators for letting users build and manipulate training datasets: labeling functions for labeling unlabeled data, transformation functions for expressing data augmentation strategies, and slicing functions for partitioning and structuring training datasets. These operators allow domain expert users to specify ML models via noisy operators over training data, leading to applications that can be built in hours or days rather than months or years. Alex explores recent work on modeling the noise and imprecision inherent in these operators and using these approaches to train ML models that solve real-world problems, including a recent state-of-the-art result on the SuperGLUE natural language processing benchmark task. Prerequisite knowledge A basic understanding of machine learning What you'll learn Discover learning techniques for building, managing, and iterating on training datasets and modeling pipelines for ML in general and using the Snorkel framework This session is from the 2019 O'Reilly Artificial Intelligence Conference in San Jose, CA.


Accelerating Machine Learning With Training Data Management

Accelerating Machine Learning with Training Data Management PDF
Author: Alexander Jason Ratner
Publisher:
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Size: 29.39 MB
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Languages : en
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Accelerating Machine Learning With Training Data Management

by Alexander Jason Ratner, Accelerating Machine Learning With Training Data Management Books available in PDF, EPUB, Mobi Format. Download Accelerating Machine Learning With Training Data Management books, One of the biggest bottlenecks in developing machine learning applications today is the need for large hand-labeled training datasets. Even at the world's most sophisticated technology companies, and especially at other organizations across science, medicine, industry, and government, the time and monetary cost of labeling and managing large training datasets is often the blocking factor in using machine learning. In this thesis, we describe work on training data management systems that enable users to programmatically build and manage training datasets, rather than labeling and managing them by hand, and present algorithms and supporting theory for automatically modeling this noisier process of training set specification in order to improve the resulting training set quality. We then describe extensive empirical results and real-world deployments demonstrating that programmatically building, managing, and modeling training sets in this way can lead to radically faster, more flexible, and more accessible ways of developing machine learning applications. We start by describing data programming, a paradigm for labeling training datasets programmatically rather than by hand, and Snorkel, an open source training data management system built around data programming that has been used by major technology companies, academic labs, and government agencies to build machine learning applications in days or weeks rather than months or years. In Snorkel, rather than hand-labeling training data, users write programmatic operators called labeling functions, which label data using various heuristic or weak supervision strategies such as pattern matching, distant supervision, and other models. These labeling functions can have noisy, conflicting, and correlated outputs, which Snorkel models and combines into clean training labels without requiring any ground truth using theoretically consistent modeling approaches we develop. We then report on extensive empirical validations, user studies, and real-world applications of Snorkel in industrial, scientific, medical, and other use cases ranging from knowledge base construction from text data to medical monitoring over image and video data. Next, we will describe two other approaches for enabling users to programmatically build and manage training datasets, both currently integrated into the Snorkel open source framework: Snorkel MeTaL, an extension of data programming and Snorkel to the setting where users have multiple related classification tasks, in particular focusing on multi-task learning; and TANDA, a system for optimizing and managing strategies for data augmentation, a critical training dataset management technique wherein a labeled dataset is artificially expanded by transforming data points. Finally, we will conclude by outlining future research directions for further accelerating and democratizing machine learning workflows, such as higher-level programmatic interfaces and massively multi-task frameworks.


O Reilly Artificial Intelligence Conference 2019 San Jose California

O Reilly Artificial Intelligence Conference 2019   San Jose  California PDF
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O Reilly Artificial Intelligence Conference 2019 San Jose California

by , O Reilly Artificial Intelligence Conference 2019 San Jose California Books available in PDF, EPUB, Mobi Format. Download O Reilly Artificial Intelligence Conference 2019 San Jose California books, The O'Reilly Artificial Intelligence Conference San Jose 2019 was some of the world's top AI practitioners sharing their AI passion and AI knowledge with thousands of attendees. It was Uber AI Lab's Kenneth Stanley illuminating the future of AI with his talk about open-endedness learning. It was Danny Lange (Unity Technologies) on game environments that test the capabilities of AI-trained agents; Yi Zhang (University of California, Santa Cruz) on chatbots and the nearness of true conversational computing; and Hagay Lupesko (Facebook) on the challenges of mega-scale, deep learning-based personalization modeling. In short, AI San Jose 2019 was a mind-blower and this video compilation gives you access to virtually all of it with hours of material to peruse, study, and absorb on your own schedule. Highlights include: Complete video recordings of the best of AI San Jose 2019's keynote addresses, deep dive tutorials, and technical sessions. Keynote addresses from AI thought leaders such as Andrew Feldman (Cerebras Systems), Sahika Genc (AWS DeepRacer/SageMaker RL), and Mike Jordan (UC Berkeley). Unrestricted access to the exclusive AI Business Summit's executive briefings, best practice sessions, and tutorials led by AI business pros such as Michael Radwin (Intuit), Bahman Bahmani (Rakuten), Mayukh Bhaowal (Salesforce Einstein), Yael Gozin (Pfizer), and James Manyika (McKinsey & Company). Deep dive tutorials, including Jason Dai (Intel) on building deep learning apps for big data with the Analytics Zoo AI platform; Chaoran Yu (Lightbend) on doing machine learning (ML) with Kafka-based streaming pipelines; and Justina Petraityte (Rasa) on developing intelligent AI assistants based entirely on ML with open source Rasa NLU and Rasa Core. Sessions devoted to AI Implementation, such as Anuradha Gali (Uber) on using AI to leverage 15 million trips a day on the Uber platform; Roshan Sumbaly (Facebook) on connecting the dots between the software engineering and ML development worlds; Paige Bailey's (Google) on TensorFlow 2.0's new features; and Alex Ratner (Snorkel) on building and managing training datasets for ML with open source Snorkel. Sessions focused on AI Models & Methods, including Lukas Biewald (Weights & Biases) review of how to use Keras to classify text with LSTMs and other ML techniques; and Francesca Lazzeri (Microsoft) on using AutoML to automate ML model selection and hyperparameter tuning. Dozens of how-to-do-it sessions detailing the tec...


Practical Natural Language Processing

Practical Natural Language Processing PDF
Author: Sowmya Vajjala
Publisher: "O'Reilly Media, Inc."
ISBN: 1492054003
Size: 24.59 MB
Format: PDF
Category : Computers
Languages : en
Pages : 456
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Practical Natural Language Processing

by Sowmya Vajjala, Practical Natural Language Processing Books available in PDF, EPUB, Mobi Format. Download Practical Natural Language Processing books, Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective


The Artificial Intelligence Imperative A Practical Roadmap For Business

The Artificial Intelligence Imperative  A Practical Roadmap for Business PDF
Author: Anastassia Lauterbach
Publisher: ABC-CLIO
ISBN: 1440859957
Size: 30.81 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 290
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The Artificial Intelligence Imperative A Practical Roadmap For Business

by Anastassia Lauterbach, The Artificial Intelligence Imperative A Practical Roadmap For Business Books available in PDF, EPUB, Mobi Format. Download The Artificial Intelligence Imperative A Practical Roadmap For Business books, This practical guide to artificial intelligence and its impact on industry dispels common myths and calls for cross-sector, collaborative leadership for the responsible design and embedding of AI in the daily work of businesses and oversight by boards. • Provides a strategic framework for corporate boards and executive leadership teams to remain competitive in the age of AI • Offers practical and clear advice on AI and machine learning, introducing technical concepts and translating research trends into practical applications while simultaneously incorporating critical governance, ethics, sustainability, and risk considerations • Provides traditional businesses and their boards with practical questions to ask their teams, suppliers, and technology partners and offers guidance on market trends and players to which to pay attention


Weakly Supervised Learning

Weakly Supervised Learning PDF
Author: Russell Jurney
Publisher: O'Reilly Media
ISBN: 9781492077060
Size: 16.73 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 200
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Weakly Supervised Learning

by Russell Jurney, Weakly Supervised Learning Books available in PDF, EPUB, Mobi Format. Download Weakly Supervised Learning books, Build products using deep learning, weakly supervised learning, and natural language processing without collecting millions of training records. This practical book explains how and provides a how-to guide for actually shipping deep learning models--since most of these projects never leave the lab. Deep networks have enabled new applications using unstructured data to proliferate, but much of the work means collecting millions of records as well as labeled datasets. Author Russell Jurney from Data Syndrome helps machine-learning engineers, software engineers, deep learning engineers, and data scientists learn practical applications using several weakly supervised learning methods. You'll explore: Semi-supervised learning: Combine a small amount of labeled data with a large amount of unlabeled data to train an improved final model Transfer learning: Re-train existing models from a related domain using training data from the problem domain Distant supervision: Combine low-quality labels from databases and other sources to create high-quality labels for the entire dataset Model versioning and management: start with a small labeled dataset and create a production grade model from concept through deployment


Ecppm 2021 Ework And Ebusiness In Architecture Engineering And Construction

ECPPM 2021   eWork and eBusiness in Architecture  Engineering and Construction PDF
Author: Vitaly Semenov
Publisher: CRC Press
ISBN: 1000413322
Size: 15.44 MB
Format: PDF
Category : Technology & Engineering
Languages : en
Pages : 596
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Ecppm 2021 Ework And Ebusiness In Architecture Engineering And Construction

by Vitaly Semenov, Ecppm 2021 Ework And Ebusiness In Architecture Engineering And Construction Books available in PDF, EPUB, Mobi Format. Download Ecppm 2021 Ework And Ebusiness In Architecture Engineering And Construction books, eWork and eBusiness in Architecture, Engineering and Construction 2021 collects the papers presented at the 13th European Conference on Product and Process Modelling (ECPPM 2021, Moscow, 5-7 May 2021). The contributions cover a wide spectrum of thematic areas that hold great promise towards the advancement of research and technological development targeted at the digitalization of the AEC/FM (Architecture, Engineering, Construction and Facilities Management) domains. High quality contributions are devoted to critically important problems that arise, including: Information and Knowledge Management Semantic Web and Linked Data Communication and Collaboration Technologies Software Interoperability BIM Servers and Product Lifecycle Management Systems Digital Twins and Cyber-Physical Systems Sensors and Internet of Things Big Data Artificial and Augmented Intelligence in AEC Construction Management 5D/nD Modelling and Planning Building Performance Simulation Contract, Cost and Risk Management Safety and Quality Sustainable Buildings and Urban Environments Smart Buildings and Cities BIM Standardization, Implementation and Adoption Regulatory and Legal Aspects BIM Education and Training Industrialized Production, Smart Products and Services Over the past quarter century, the biennial ECPPM conference series, as the oldest BIM conference, has provided researchers and practitioners with a unique platform to present and discuss the latest developments regarding emerging BIM technologies and complementary issues for their adoption in the AEC/FM industry.


Das Devops Handbuch

Das DevOps Handbuch PDF
Author: Gene Kim
Publisher: O'Reilly
ISBN: 3960101244
Size: 28.24 MB
Format: PDF, ePub
Category : Computers
Languages : de
Pages : 432
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Das Devops Handbuch

by Gene Kim, Das Devops Handbuch Books available in PDF, EPUB, Mobi Format. Download Das Devops Handbuch books, Mehr denn je ist das effektive Management der IT entscheidend für die Wettbewerbsfähigkeit von Organisationen. Viele Manager in softwarebasierten Unternehmen ringen damit, eine Balance zwischen Agilität, Zuverlässigkeit und Sicherheit ihrer Systeme herzustellen. Auf der anderen Seite schaffen es High-Performer wie Google, Amazon, Facebook oder Netflix, routinemäßig und zuverlässig hundertoder gar tausendmal pro Tag Code auszuliefern. Diese Unternehmen verbindet eins: Sie arbeiten nach DevOps-Prinzipien. Die Autoren dieses Handbuchs folgen den Spuren des Romans Projekt Phoenix und zeigen, wie die DevOps-Philosophie praktisch implementiert wird und Unternehmen dadurch umgestaltet werden können. Sie beschreiben konkrete Tools und Techniken, die Ihnen helfen, Software schneller und sicherer zu produzieren. Zudem stellen sie Ihnen Maßnahmen vor, die die Zusammenarbeit aller Abteilungen optimieren, die Arbeitskultur verbessern und die Profitabilität Ihres Unternehmens steigern können. Themen des Buchs sind: Die Drei Wege: Die obersten Prinzipien, von denen alle DevOps-Maßnahmen abgeleitet werden. Einen Ausgangspunkt finden: Eine Strategie für die DevOps-Transformation entwickeln, Wertketten und Veränderungsmuster kennenlernen, Teams schützen und fördern. Flow beschleunigen: Den schnellen Fluss der Arbeit von Dev hin zu Ops ermöglichen durch eine optimale Deployment-Pipeline, automatisierte Tests, Continuous Integration und Continuous Delivery. Feedback verstärken: Feedback-Schleifen verkürzen und vertiefen, Telemetriedaten erzeugen und Informationen unternehmensweit sichtbar machen. Kontinuierliches Lernen ermöglichen: Eine Just Culture aufbauen und ausreichend Zeit reservieren, um das firmenweite Lernen zu fördern.


Data Science Mit Python

Data Science mit Python PDF
Author: Jake VanderPlas
Publisher: MITP-Verlags GmbH & Co. KG
ISBN: 3958456979
Size: 56.27 MB
Format: PDF, ePub
Category : Computers
Languages : de
Pages : 552
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Data Science Mit Python

by Jake VanderPlas, Data Science Mit Python Books available in PDF, EPUB, Mobi Format. Download Data Science Mit Python books, Die wichtigsten Tools für die Datenanalyse und-bearbeitung im praktischen Einsatz Python effizient für datenintensive Berechnungen einsetzen mit IPython und Jupyter Laden, Speichern und Bearbeiten von Daten und numerischen Arrays mit NumPy und Pandas Visualisierung von Daten mit Matplotlib Python ist für viele die erste Wahl für Data Science, weil eine Vielzahl von Ressourcen und Bibliotheken zum Speichern, Bearbeiten und Auswerten von Daten verfügbar ist. In diesem Buch erläutert der Autor den Einsatz der wichtigsten Tools. Für Datenanalytiker und Wissenschaftler ist dieses umfassende Handbuch von unschätzbarem Wert für jede Art von Berechnung mit Python sowie bei der Erledigung alltäglicher Aufgaben. Dazu gehören das Bearbeiten, Umwandeln und Bereinigen von Daten, die Visualisierung verschiedener Datentypen und die Nutzung von Daten zum Erstellen von Statistiken oder Machine-Learning-Modellen. Dieses Handbuch erläutert die Verwendung der folgenden Tools: ● IPython und Jupyter für datenintensive Berechnungen ● NumPy und Pandas zum effizienten Speichern und Bearbeiten von Daten und Datenarrays in Python ● Matplotlib für vielfältige Möglichkeiten der Visualisierung von Daten ● Scikit-Learn zur effizienten und sauberen Implementierung der wichtigsten und am meisten verbreiteten Algorithmen des Machine Learnings Der Autor zeigt Ihnen, wie Sie die zum Betreiben von Data Science verfügbaren Pakete nutzen, um Daten effektiv zu speichern, zu handhaben und Einblick in diese Daten zu gewinnen. Grundlegende Kenntnisse in Python werden dabei vorausgesetzt. Leserstimme zum Buch: »Wenn Sie Data Science mit Python betreiben möchten, ist dieses Buch ein hervorragender Ausgangspunkt. Ich habe es sehr erfolgreich beim Unterrichten von Informatik- und Statistikstudenten eingesetzt. Jake geht weit über die Grundlagen der Open-Source-Tools hinaus und erläutert die grundlegenden Konzepte, Vorgehensweisen und Abstraktionen in klarer Sprache und mit verständlichen Erklärungen.« – Brian Granger, Physikprofessor, California Polytechnic State University, Mitbegründer des Jupyter-Projekts


Machine Learning Mit Python Das Praxis Handbuch Fur Data Science Predictive Analytics Und Deep Learning

MACHINE LEARNING MIT PYTHON DAS PRAXIS HANDBUCH FUR DATA SCIENCE  PREDICTIVE ANALYTICS UND DEEP LEARNING  PDF
Author: SEBASTIAN RASCHKA.
Publisher:
ISBN: 9783958454231
Size: 51.72 MB
Format: PDF, Docs
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Languages : de
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Machine Learning Mit Python Das Praxis Handbuch Fur Data Science Predictive Analytics Und Deep Learning

by SEBASTIAN RASCHKA., Machine Learning Mit Python Das Praxis Handbuch Fur Data Science Predictive Analytics Und Deep Learning Books available in PDF, EPUB, Mobi Format. Download Machine Learning Mit Python Das Praxis Handbuch Fur Data Science Predictive Analytics Und Deep Learning books,


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